Principal Consultant – Analytics, Credit Strategy
Posted 2026-05-05
Remote, USA
Full-time
Immediate Start
- Job Description:
- Be the day‑to‑day analytics partner for clients on credit strategy, risk optimization, and portfolio performance
- Translate client goals into clear analytical questions, project plans, and structured workflows
- Use Python and SQL to explore data, validate hypotheses, and support analytical workflows developed by Data Science teams
- Contribute to the development of credit strategies, policy rules, and models across underwriting, account management, pricing, and collections
- Conduct segmentation and performance deep dives to identify applicable client opportunities
- Interpret model outputs and analytical findings, turning them into clear recommendations aligned with client goals and constraints
- Produce client‑ready deliverables, including presentations, dashboards, summaries, and executive readouts
- Present insights to client partners, including risk, analytics, and business leaders
- Support Sales and Account teams with pre‑sales analytics, POVs, and proposal inputs
- Work with our teams (Data Science, Product, Engineering) to ensure client requirements are understood and delivered
- Support post‑implementation work such as monitoring, performance tracking, and strategy optimization
- Ensure analytical work follows data quality, governance, and regulatory expectations
- Requirements:
- 3–6 years of experience in analytics, consulting, credit risk, or financial services
- Proficiency in Python (Pandas, NumPy, basic modeling/visualization) for analysis
- SQL skills for querying, validating, and analyzing large datasets
- Familiarity with credit risk, portfolio analytics, and the credit lifecycle
- Experienced working with scores, attributes, segments, and performance metrics
- Convert analytical results into clear, business‑focused recommendations
- Experienced working directly with clients or partners in consulting or professional services
- Experienced in credit risk, FinTech, or decisioning platforms
- Familiarity with model performance metrics (AUC, KS, lift, stability, and bad‑rate curves)
- Experienced supporting machine learning or scorecard‑based model development
- Exposure to visualization tools (Tableau, Power BI, Looker)
- Experienced supporting pre‑sales, pilots, or proof‑of‑value engagements
- Benefits:
- Great compensation package
- Core benefits including medical, dental, vision, and matching 401K
- Flexible work environment, ability to work remote, hybrid or in-office
- Flexible time off including volunteer time off, vacation, sick and 12-paid holidays